I-TASSER-MR: automated molecular replacement for distant-homology proteins using iterative fragment assembly and progressive sequence truncation

Application of Computational Techniques in Antibody Fc-Fused Molecule Design for Therapeutics

Since the advent of hybridoma technology in the year 1975, it took a decade to witness the first approved monoclonal antibody Orthoclone OKT39 (muromonab-CD3) in the year 1986. Since then, continuous strides have been made to engineer antibodies for specific desired effects. The engineering efforts were not confined to only the variable domains of the antibody but also included the fragment crystallizable (Fc) region that influences the immune response and serum half-life. Engineering of the Fc fragment would have a profound effect on the therapeutic dose, antibody-dependent cell-mediated cytotoxicity as well as antibody-dependent cellular phagocytosis. The integration of computational techniques into antibody engineering designs has allowed for the generation of testable hypotheses and guided the rational antibody design framework prior to further experimental evaluations. In this article, we discuss the recent works in the Fc-fused molecule design that involves computational techniques. We also summarize the usefulness of in silico techniques to aid Fc-fused molecule design and analysis for the therapeutics application.

Accelerating crystal structure determination with iterative AlphaFold prediction

Experimental structure determination can be accelerated with artificial intelligence (AI)-based structure-prediction methods such as AlphaFold. Here, an automatic procedure requiring only sequence information and crystallographic data is presented that uses AlphaFold predictions to produce an electron-density map and a structural model. Iterating through cycles of structure prediction is a key element of this procedure: a predicted model rebuilt in one cycle is used as a template for prediction in the next cycle. This procedure was applied to X-ray data for 215 structures released by the Protein Data Bank in a recent six-month period. In 87% of cases our procedure yielded a model with at least 50% of Cα atoms matching those in the deposited models within 2 Å. Predictions from the iterative template-guided prediction procedure were more accurate than those obtained without templates. It is concluded that AlphaFold predictions obtained based on sequence information alone are usually accurate enough to solve the crystallographic phase problem with molecular replacement, and a general strategy for macromolecular structure determination that includes AI-based prediction both as a starting point and as a method of model optimization is suggested.

Reducing the Immunogenicity of Pulchellin A-Chain, Ribosome-Inactivating Protein Type 2, by Computational Protein Engineering for Potential New Immunotoxins

Pulchellin is a plant biotoxin categorized as a type 2 ribosome-inactivating protein (RIPs) which potentially kills cells at very low concentrations. Biotoxins serve as targeting immunotoxins (IT), consisting of antibodies conjugated to toxins. ITs have two independent protein components, a human antibody and a toxin with a bacterial or plant source; therefore, they pose unique setbacks in immunogenicity. To overcome this issue, the engineering of epitopes is one of the beneficial methods to elicit an immunological response. Here, we predicted the tertiary structure of the pulchellin A-chain (PAC) using five common powerful servers and adopted the best model after refining. Then, predicted structure using four distinct computational approaches identified conformational B-cell epitopes. This approach identified some amino acids as a potential for lowering immunogenicity by point mutation. All mutations were then applied to generate a model of pulchellin containing all mutations (so-called PAM). Mutants’ immunogenicity was assessed and compared to the wild type as well as other mutant characteristics, including stability and compactness, were computationally examined in addition to immunogenicity. The findings revealed a reduction in immunogenicity in all mutants and significantly in N146V and R149A. Furthermore, all mutants demonstrated remarkable stability and validity in Molecular Dynamic (MD) simulations. During docking and simulations, the most homologous toxin to pulchellin, Abrin-A was applied as a control. In addition, the toxin candidate containing all mutations (PAM) disclosed a high level of stability, making it a potential model for experimental deployment. In conclusion, by eliminating B-cell epitopes, our computational approach provides a potential less immunogenic IT based on PAC.

The chemistry of snake venom and its medicinal potential

The fascination and fear of snakes dates back to time immemorial, with the first scientific treatise on snakebite envenoming, the Brooklyn Medical Papyrus, dating from ancient Egypt. Owing to their lethality, snakes have often been associated with images of perfidy, treachery and death. However, snakes did not always have such negative connotations. The curative capacity of venom has been known since antiquity, also making the snake a symbol of pharmacy and medicine. Today, there is renewed interest in pursuing snake-venom-based therapies. This Review focuses on the chemistry of snake venom and the potential for venom to be exploited for medicinal purposes in the development of drugs. The mixture of toxins that constitute snake venom is examined, focusing on the molecular structure, chemical reactivity and target recognition of the most bioactive toxins, from which bioactive drugs might be developed. The design and working mechanisms of snake-venom-derived drugs are illustrated, and the strategies by which toxins are transformed into therapeutics are analysed. Finally, the challenges in realizing the immense curative potential of snake venom are discussed, and chemical strategies by which a plethora of new drugs could be derived from snake venom are proposed.

Profiles of Natural and Designed Protein-Like Sequences Effectively Bridge Protein Sequence Gaps: Implications in Distant Homology Detection

Sequence-based approaches are fundamental to guide experimental investigations in obtaining structural and/or functional insights into uncharacterized protein families. Powerful profile-based sequence search methods rely on a sequence space continuum to identify non-trivial relationships through homology detection. The computational design of protein-like sequences that serve as "artificial linkers" is useful in identifying relationships between distant members of a structural fold. Such sequences act as intermediates and guide homology searches between distantly related proteins. Here, we describe an approach that represents natural intermediate sequences and designed protein-like sequences as HMM (Hidden Markov Models) profiles, to improve the sensitivity of existing search methods. Searches made within the "Profile database" were shown to recognize the parent structural fold for 90% of the search queries at query coverage better than 60%. For 1040 protein families with no available structure, fold associations were made through searches in the database of natural and designed sequence profiles. Most of the associations were made with the Alpha-alpha superhelix, Transmembrane beta-barrels, TIM barrel, and Immunoglobulin-like beta-sandwich folds. For 11 domain families of unknown functions, we provide confident fold associations using the profiles of designed sequences and a consensus from other fold recognition methods. For two DUFs (Domain families of Unknown Functions), we performed detailed functional annotation through comparisons with characterized templates of families of known function.

Implications of AlphaFold2 for crystallographic phasing by molecular replacement

The AlphaFold2 results in the 14th edition of Critical Assessment of Structure Prediction (CASP14) showed that accurate (low root-mean-square deviation) in silico models of protein structure domains are on the horizon, whether or not the protein is related to known structures through high-coverage sequence similarity. As highly accurate models become available, generated by harnessing the power of correlated mutations and deep learning, one of the aspects of structural biology to be impacted will be methods of phasing in crystallography. Here, the data from CASP14 are used to explore the prospects for changes in phasing methods, and in particular to explore the prospects for molecular-replacement phasing using in silico models.

Evidence for the Involvement of Pleckstrin Homology Domain-Containing Proteins in the Transport of Enterocin DD14 (EntDD14); a Leaderless Two-Peptide Bacteriocin

Bacteriocins synthesis is initiated from an inactive precursor, which is composed of an N-terminal leader peptide attached to a C-terminal pro-peptide. However, leaderless bacteriocins (LLB) do not possess this N-terminal leader peptide nor undergo post-translational modifications. These atypical bacteriocins are observed to be immediately active after their translation in the cytoplasm. However, although considered to be simple, the biosynthetic pathway of LLB remains to be fully understood. Enterocin DD14 (EntDD14) is a two-peptide LLB produced by Enterococcus faecalis 14, which is a strain isolated from meconium. In silico analysis of DNA encoding EntDD14 located a cluster of 10 genes ddABCDEFGHIJ, where ddE and ddF encode the peculiar DdE and DdF proteins, carrying pleckstrin homology (PH) domains. These modules are quite common in Eucarya proteins and are known to be involved in intracellular signaling or cytoskeleton organization. To elucidate their role within the EntDD14 genetic determinants, we constructed deletion mutants of the ddE and ddF genes. As a result, the mutants were unable to export EntDD14 outside of the cytoplasm even though there was a clear expression of structural genes ddAB encoding EntDD14, and genes ddHIJ encoding an ABC transporter. Importantly, in these mutant strains (ΔddE and ΔddF), EntDD14 was detected by mass spectrometry in the intracellular soluble fraction exerting, upon its accumulation, a toxic effect on the producing strain as revealed by cell-counting and confocal microscopy analysis. Taken together, these results clearly indicate that PH domain-containing proteins, such as DdE and DdF, are involved in the transport of the leaderless two-peptide EntDD14.

Accurate prediction of protein structures and interactions using a three-track neural network

DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track network in which information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging x-ray crystallography and cryo-electron microscopy structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches that require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research.

The coordination of major events in C4 photosynthesis evolution in the genus Flaveria

C4 photosynthesis is a remarkable complex trait, elucidations of the evolutionary trajectory of C4 photosynthesis from its ancestral C3 pathway can help us better understand the generic principles of the evolution of complex traits and guide the engineering of C3 crops for higher yields. Here, we used the genus Flaveria that contains C3, C3-C4, C4-like and C4 species as a system to study the evolution of C4 photosynthesis. We first mapped transcript abundance, protein sequence and morphological features onto the phylogenetic tree of the genus Flaveria, and calculated the evolutionary correlation of different features; we then predicted the relative changes of ancestral nodes of those features to illustrate the major events during the evolution of C4 photosynthesis. We found that gene expression and protein sequence showed consistent modification patterns in the phylogenetic tree. High correlation coefficients ranging from 0.46 to 0.9 among gene expression, protein sequence and morphology were observed. The greatest modification of those different features consistently occurred at the transition between C3-C4 species and C4-like species. Our results show highly coordinated changes in gene expression, protein sequence and morphological features, which support evolutionary major events during the evolution of C4 metabolism.

Molecular-replacement phasing using predicted protein structures from AWSEM-Suite

The phase problem in X-ray crystallography arises from the fact that only the intensities, and not the phases, of the diffracting electromagnetic waves are measured directly. Molecular replacement can often estimate the relative phases of reflections starting with those derived from a template structure, which is usually a previously solved structure of a similar protein. The key factor in the success of molecular replacement is finding a good template structure. When no good solved template exists, predicted structures based partially on templates can sometimes be used to generate models for molecular replacement, thereby extending the lower bound of structural and sequence similarity required for successful structure determination. Here, the effectiveness is examined of structures predicted by a state-of-the-art prediction algorithm, the Associative memory, Water-mediated, Structure and Energy Model Suite (AWSEM-Suite), which has been shown to perform well in predicting protein structures in CASP13 when there is no significant sequence similarity to a solved protein or only very low sequence similarity to known templates. The performance of AWSEM-Suite structures in molecular replacement is discussed and the results show that AWSEM-Suite performs well in providing useful phase information, often performing better than I-TASSER-MR and the previous algorithm AWSEM-Template.

Uncovering a superfamily of nickel-dependent hydroxyacid racemases and epimerases

Isomerization reactions are fundamental in biology. Lactate racemase, which isomerizes L- and D-lactate, is composed of the LarA protein and a nickel-containing cofactor, the nickel-pincer nucleotide (NPN). In this study, we show that LarA is part of a superfamily containing many different enzymes. We overexpressed and purified 13 lactate racemase homologs, incorporated the NPN cofactor, and assayed the isomerization of different substrates guided by gene context analysis. We discovered two malate racemases, one phenyllactate racemase, one α-hydroxyglutarate racemase, two D-gluconate 2-epimerases, and one short-chain aliphatic α-hydroxyacid racemase among the tested enzymes. We solved the structure of a malate racemase apoprotein and used it, along with the previously described structures of lactate racemase holoprotein and D-gluconate epimerase apoprotein, to identify key residues involved in substrate binding. This study demonstrates that the NPN cofactor is used by a diverse superfamily of α-hydroxyacid racemases and epimerases, widely expanding the scope of NPN-dependent enzymes.

The Hirudo Medicinalis Microbiome Is a Source of New Antimicrobial Peptides

Antimicrobial peptides (AMPs) are considered a promising new class of anti-infectious agents. This study reports new antimicrobial peptides derived from the Hirudo medicinalis microbiome identified by a computational analysis method applied to the H. medicinalis metagenome. The identified AMPs possess a strong antimicrobial activity against Gram-positive and Gram-negative bacteria (MIC range: 5.3 to 22.4 μM), including Staphylococcus haemolyticus, an opportunistic coagulase-negative pathogen. The secondary structure analysis of peptides via CD spectroscopy showed that all the AMPs except pept_352 have mostly disordered structures that do not change under different conditions. For peptide pept_352, the α-helical content increases in the membrane environment. The examination of the mechanism of action of peptides suggests that peptide pept_352 exhibits a direct membranolytic activity. Furthermore, the cytotoxicity assay demonstrated that the nontoxic peptide pept_1545 is a promising candidate for drug development. Overall, the analysis method implemented in the study may serve as an effective tool for the identification of new AMPs.

Computational Analysis of IDH1, IDH2, and TP53 Mutations in Low-Grade Gliomas Including Oligodendrogliomas and Astrocytomas

Introduction:

The emergence of new omics approaches, such as genomic algorithms to identify tumor mutations and molecular modeling tools to predict the three-dimensional structure of proteins, has facilitated the understanding of the dynamic mechanisms involved in the pathogenesis of low-grade gliomas including oligodendrogliomas and astrocytomas.

Methods:

In this study, we targeted known mutations involved in low-grade gliomas, starting with the sequencing of genomic regions encompassing exon 4 of isocitrate dehydrogenase 1 (IDH1) and isocitrate dehydrogenase 2 (IDH2) and the four exons (5-6 and 7-8) of TP53 from 32 samples, followed by computational analysis to study the impact of these mutations on the structure and function of 3 proteins IDH1, IDH2, and p53.

Results:

We obtain a mutation that has an effect on the catalytic site of the protein IDH1 as R132H and on the catalytic site of the protein IDH2 as R172M. Other mutations at p53 have been identified as K305N, which is a pathogenic mutation; R175 H, which is a benign mutation; and R158G, which disrupts the structural conformation of the tumor suppressor protein.

Conclusion:

In low-grade gliomas, mutations in IDH1, IDH2, and TP53 may be the key to tumor progression because they have an effect on the function of the protein such as mutations R132H in IDH1 and R172M in IDH2, which change the function of the enzyme alpha-ketoglutarate, or R158G in TP53, which affects the structure of the generated protein, thus their importance in understanding gliomagenesis and for more accurate diagnosis complementary to the anatomical pathology tests.

Crystal structures and biochemical analyses of the bacterial arginine dihydrolase ArgZ suggests a "bond rotation" catalytic mechanism

A recently discovered ornithine-ammonia cycle (OAC) serves as a conduit in the nitrogen storage and remobilization machinery in cyanobacteria. The OAC involves an arginine catabolic reaction catalyzed by the arginine dihydrolase ArgZ whose catalytic mechanism is unknown. Here we determined the crystal structures at 1.2-3.0 Å of unliganded ArgZ from the cyanobacterium Synechocystis sp. PCC6803 and of ArgZ complexed with its substrate arginine, a covalently linked reaction intermediate, or the reaction product ornithine. The structures reveal that a key residue, Asn⁷¹, in the ArgZ active center functions as the determinant distinguishing ArgZ from other members of the guanidino group-modifying enzyme superfamily. The structures, along with biochemical evidence from enzymatic assays coupled with electrospray ionization MS techniques, further suggest that ArgZ-catalyzed conversion of arginine to ornithine, ammonia, and carbon dioxide consists of two successive cycles of amine hydrolysis. Finally, we show that arginine dihydrolases are broadly distributed among bacteria and metazoans, suggesting that the OAC may be frequently used for redistribution of nitrogen from arginine catabolism or nitrogen fixation.

A novel de novo nonsense mutation in ZC4H2 causes Wieacker-Wolff Syndrome

Background

Wieacker‐Wolff syndrome (WWS) is a congenital X‐linked neuromuscular disorder, which was firstly reported in 1985. Zinc finger C4H2‐type containing (ZC4H2) gene has been found to be associated with the disease pathogenesis. However, the underlying mechanism remains elusive.

Methods

Whole‐exome sequencing was performed to identify the mutations. Expression plasmids were constructed and cell culture and immune‐biochemical assays were used to examine the effects of the mutation.

Results

We reported a female patient with classical symptoms of WWS and discovered a novel nonsense heterozygous mutation (p.R67X; c.199C>T) in ZC4H2 gene in the patient but not in her parents. The mutation resulted in a 66 amino‐acid truncated ZC4H2 protein. The mutation is located in the key helix domain and it altered the subcellular locations of the mutant ZC4H2 protein. X‐chromosome inactivation (XCI) pattern analysis revealed that the XCI ratio of the proband was 22:78.

Conclusion

Female heterozygous carriers with nonsense mutation with a truncated ZC4H2 protein could lead to the pathogenesis of Wieacker‐Wolff syndrome and our study provides a potential new target for the disease treatment.

The In Silico Drug Discovery Toolbox: Applications in Lead Discovery and Optimization

BACKGROUND

Discovery and development of a new drug is a long lasting and expensive journey that takes around 20 years from starting idea to approval and marketing of new medication. Despite R&D expenditures have been constantly increasing in the last few years, the number of new drugs introduced into market has been steadily declining. This is mainly due to preclinical and clinical safety issues, which still represent about 40% of drug discontinuation. To cope with this issue, a number of in silico techniques are currently being used for an early stage evaluation/prediction of potential safety issues, allowing to increase the drug-discovery success rate and reduce costs associated with the development of a new drug.

METHODS

In the present review, we will analyse the early steps of the drug-discovery pipeline, describing the sequence of steps from disease selection to lead optimization and focusing on the most common in silico tools used to assess attrition risks and build a mitigation plan.

RESULTS

A comprehensive list of widely used in silico tools, databases, and public initiatives that can be effectively implemented and used in the drug discovery pipeline has been provided. A few examples of how these tools can be problem-solving and how they may increase the success rate of a drug discovery and development program have been also provided. Finally, selected examples where the application of in silico tools had effectively contributed to the development of marketed drugs or clinical candidates will be given.

CONCLUSION

The in silico toolbox finds great application in every step of early drug discovery: (i) target identification and validation; (ii) hit identification; (iii) hit-to-lead; and (iv) lead optimization. Each of these steps has been described in details, providing a useful overview on the role played by in silico tools in the decision-making process to speed-up the discovery of new drugs.

In silico analysis of nonsynonymous single-nucleotide polymorphisms (nsSNPs) of the SMPX gene

Mutations in the SMPX gene can disrupt the regular activity of the SMPX protein, which is involved in the hearing process. Recent reports showing a link between nonsynonymous single-nucleotide polymorphisms (nsSNPs) in SMPX and hearing loss, thus classifying deleterious SNPs in SMPX will be an uphill task before designing a more extensive population study. In this study, damaging nsSNPs of SMPX from the dbSNP database were identified by using 13 bioinformatics tools. Initially, the impact of nsSNPs in the SMPX gene were evaluated through different in silico predictors; and the deleterious convergent changes were analyzed by energy-minimization-guided residual network analysis. In addition, the pathogenic effects of mutations in SMPX-mediated protein-protein interactions were also characterized by structural modeling and binding energy calculations. A total of four mutations (N19D, A29T, K54N, and S71L) were found to be highly deleterious by all the tools, which are located at highly conserved regions. Furthermore, all four mutants showed structural alterations, and the communities of amino acids for mutant proteins were readily changed, compared to the wild-type. Among them, A29T (rs772775896) was revealed as the most damaging nsSNP, which caused significant structural deviation of the SMPX protein, as a result reducing the binding affinity to other functional partners. These findings reflect the computational insights into the deleterious role of nsSNPs in SMPX, which might be helpful for subjecting wet-lab confirmatory analysis.

I-TASSER gateway: A protein structure and function prediction server powered by XSEDE

There is an increasing gap between the number of known protein sequences and the number of proteins with experimentally characterized structure and function. To alleviate this issue, we have developed the I-TASSER gateway, an online server for automated and reliable protein structure and function prediction. For a given sequence, I-TASSER starts with template recognition from a known structure library, followed by full-length atomic model construction by iterative assembly simulations of the continuous structural fragments excised from the template alignments. Functional insights are then derived from comparative matching of the predicted model with a library of proteins with known function. The I-TASSER pipeline has been recently integrated with the XSEDE Gateway system to accommodate pressing demand from the user community and increasing computing costs. This report summarizes the configuration of the I-TASSER Gateway with the XSEDE-Comet supercomputer cluster, together with an overview of the I-TASSER method and milestones of its development.

Evaluation of template-based modeling in CASP13

Performance in the template‐based modeling (TBM) category of CASP13 is assessed here, using a variety of metrics. Performance of the predictor groups that participated is ranked using the primary ranking score that was developed by the assessors for CASP12. This reveals that the best results are obtained by groups that include contact predictions or inter‐residue distance predictions derived from deep multiple sequence alignments. In cases where there is a good homolog in the wwPDB (TBM‐easy category), the best results are obtained by modifying a template. However, for cases with poorer homologs (TBM‐hard), very good results can be obtained without using an explicit template, by deep learning algorithms trained on the wwPDB. Alternative metrics are introduced, to allow testing of aspects of structural models that are not addressed by traditional CASP metrics. These include comparisons to the main‐chain and side‐chain torsion angles of the target, and the utility of models for solving crystal structures by the molecular replacement method. The alternative metrics are poorly correlated with the traditional metrics, and it is proposed that modeling has reached a sufficient level of maturity that the best models should be expected to satisfy this wider range of criteria.

MultitaskProtDB-II: an update of a database of multitasking/moonlighting proteins

Multitasking, or moonlighting, is the capability of some proteins to execute two or more biological functions. MultitaskProtDB-II is a database of multifunctional proteins that has been updated. In the previous version, the information contained was: NCBI and UniProt accession numbers, canonical and additional biological functions, organism, monomeric/oligomeric states, PDB codes and bibliographic references. In the present update, the number of entries has been increased from 288 to 694 moonlighting proteins. MultitaskProtDB-II is continually being curated and updated. The new database also contains the following information: GO descriptors for the canonical and moonlighting functions, three-dimensional structure (for those proteins lacking PDB structure, a model was made using Itasser and Phyre), the involvement of the proteins in human diseases (78% of human moonlighting proteins) and whether the protein is a target of a current drug (48% of human moonlighting proteins). These numbers highlight the importance of these proteins for the analysis and explanation of human diseases and target-directed drug design. Moreover, 25% of the proteins of the database are involved in virulence of pathogenic microorganisms, largely in the mechanism of adhesion to the host. This highlights their importance for the mechanism of microorganism infection and vaccine design. MultitaskProtDB-II is available at http://wallace.uab.es/multitaskII.

Medicinal leech antimicrobial peptides lacking toxicity represent a promising alternative strategy to combat antibiotic-resistant pathogens

The rise of antibiotic resistance has necessitated the development of alternative strategies for the treatment of infectious diseases. Antimicrobial peptides (AMPs), components of the innate immune response in various organisms, are promising next-generation drugs against bacterial infections. The ability of the medicinal leech Hirudo medicinalis to store blood for months with little change has attracted interest regarding the identification of novel AMPs in this organism. In this study, we employed computational algorithms to the medicinal leech genome assembly to identify amino acid sequences encoding potential AMPs. Then, we synthesized twelve candidate AMPs identified by the algorithms, determined their secondary structures, measured minimal inhibitory concentrations against three bacterial species (Escherichia coli, Bacillus subtilis, and Chlamydia thrachomatis), and assayed cytotoxic and haemolytic activities. Eight of twelve candidate AMPs possessed antimicrobial activity, and only two of them, 3967 (FRIMRILRVLKL) and 536-1 (RWRLVCFLCRRKKV), exhibited inhibition of growth of all tested bacterial species at a minimal inhibitory concentration of 10 μmol. Thus, we evidence the utility of the developed computational algorithms for the identification of AMPs with low toxicity and haemolytic activity in the medicinal leech genome assembly.

Structural change in GadD2 of Listeria monocytogenes field isolates supports nisin resistance

The lantibiotic nisin is used as a food additive to effectively inactivate a broad spectrum of Gram-positive bacteria such as Listeria monocytogenes. In total, 282 L. monocytogenes field isolates from German ready-to-eat food products, food-processing environments and patient samples and 39 Listeria reference strains were evaluated for their susceptibility to nisin. The MIC₉₀ value was <1500 IU ml^-1. Whole genome sequences (WGS) of four nisin susceptible (NS; growth <200 IU ml^-1) and two nisin resistant L. monocytogenes field isolates (NR; growth >1500 IU ml^-1) of serotype IIa were analyzed for DNA sequence variants (DSVs) in genes putatively associated with NR and its regulation. WGS of NR differed from NS in the gadD2 gene encoding for the glutamate decarboxylase system (GAD). Moreover, homology modeling predicted a protein structure of GadD2 in NR that promoted a less pH dependent GAD activity and may therefore be beneficial for nisin resistance. Likewise NR had a significant faster growth rate compared to NS in presence of nisin at pH 7. In conclusion, results contributed to ongoing debate that a genetic shift in GAD supports NR state.

Characteristics and Expression Analysis of FmTCP15 under Abiotic Stresses and Hormones and Interact with DELLA Protein in Fraxinus mandshurica Rupr

The TEOSINTE BRANCHED1, CYCLOIDEA, and PROLIFERATION CELL FACTOR (TCP) transcription factor is a plant-specific gene family and acts on multiple functional genes in controlling growth, development, stress response, and the circadian clock. In this study, a class I member of the TCP family from Fraxinus mandshurica Rupr. was isolated and named FmTCP15, which encoded a protein of 362 amino acids. Protein structures were analyzed and five ligand binding sites were predicted. The phylogenetic relationship showed that FmTCP15 was most closely related to Solanaceae and Plantaginaceae. FmTCP15 was localized in the nuclei of F. mandshurica protoplast cells and highly expressed in cotyledons. The expression pattern revealed the FmTCP15 response to multiple abiotic stresses and hormone signals. Downstream genes for transient overexpression of FmTCP15 in seedlings were also investigated. A yeast two-hybrid assay confirmed that FmTCP15 could interact with DELLA proteins. FmTCP15 participated in the GA-signaling pathway, responded to abiotic stresses and hormone signals, and regulated multiple genes in these biological processes. Our study revealed the potential value of FmTCP15 for understanding the molecular mechanisms of stress and hormone signal responses.

Reoptimized UNRES Potential for Protein Model Quality Assessment

Ranking protein structure models is an elusive problem in bioinformatics. These models are evaluated on both the degree of similarity to the native structure and the folding pathway. Here, we simulated the use of the coarse-grained UNited RESidue (UNRES) force field as a tool to choose the best protein structure models for a given protein sequence among a pool of candidate models, using server data from the CASP11 experiment. Because the original UNRES was optimized for Molecular Dynamics simulations, we reoptimized UNRES using a deep feed-forward neural network, and we show that introducing additional descriptive features can produce better results. Overall, we found that the reoptimized UNRES performs better in selecting the best structures and tracking protein unwinding from its native state. We also found a relatively poor correlation between UNRES values and the model’s Template Modeling Score (TMS). This is remedied by reoptimization. We discuss some cases where our reoptimization procedure is useful.

New SNP variants of MARVELD2 (DFNB49) associated with non-syndromic hearing loss in Chinese population

Non-syndromic hearing loss (NSHL) is a common defect in humans. Variants of MARVELD2 at the DFNB49 locus have been shown to cause bilateral, moderate to profound NSHL. However, the role of MARVELD2 in NSHL susceptibility in the Chinese population has not been studied. Here we conducted a case-control study in an eastern Chinese population to profile the spectrum and frequency of MARVELD2 variants, as well as the association of MARVELD2 gene variants with NSHL. Our results showed that variants identified in the Chinese population are significantly different from those reported in Slovak, Hungarian, and Czech Roma, as well as Pakistani families. We identified 11 variants in a cohort of 283 NSHL cases. Through Sanger sequencing and bioinformatics analysis, we found that c.730G>A variant has detrimental effects in the eastern Chinese population, and may have relatively high correlation with NSHL pathogenicity.

MR-REX: molecular replacement by cooperative conformational search and occupancy optimization on low-accuracy protein models

Molecular replacement (MR) has commonly been employed to derive the phase information in protein crystal X-ray diffraction, but its success rate decreases rapidly when the search model is dissimilar to the target. MR-REX has been developed to perform an MR search by replica-exchange Monte Carlo simulations, which enables cooperative rotation and translation searches and simultaneous clash and occupancy optimization. MR-REX was tested on a set of 1303 protein structures of different accuracies and successfully placed 699 structures at positions that have an r.m.s.d. of below 2 Å to the target position, which is 10% higher than was obtained by Phaser. However, cases studies show that many of the models for which Phaser failed and MR-REX succeeded can be solved by Phaser by pruning them and using nondefault parameters. The factors effecting success and the parts of the methodology which lead to success are studied. The results demonstrate a new avenue for molecular replacement which outperforms (and has results that are complementary to) the state-of-the-art MR methods, in particular for distantly homologous proteins.

Use of designed sequences in protein structure recognition

Background

Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure.

Results

We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation.

Conclusion

The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as ‘linkers’, where natural linkers between distant proteins are unavailable.

Reviewers

This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

Electronic supplementary material

The online version of this article (10.1186/s13062-018-0209-6) contains supplementary material, which is available to authorized users.

From in silico to in vitro: a trip to reveal flavonoid binding on the Rattus norvegicus Kir6.1 ATP-sensitive inward rectifier potassium channel

Background

ATP-sensitive inward rectifier potassium channels (Kir), are a potassium channel family involved in many physiological processes. K_ATP dysfunctions are observed in several diseases such as hypoglycaemia, hyperinsulinemia, Prinzmetal angina–like symptoms, cardiovascular diseases.

Methods

A broader view of the K_ATP mechanism is needed in order to operate on their regulation, and in this work we clarify the structure of the Rattus norvegicus ATP-sensitive inward rectifier potassium channel 8 (Kir6.1), which has been obtained through a homology modelling procedure. Due to the medical use of flavonoids, a considerable increase in studies on their influence on human health has recently been observed, therefore our aim is to study, through computational methods, the three-dimensional (3D) conformation together with mechanism of action of Kir6.1 with three flavonoids.

Results

Computational analysis by performing molecular dynamics (MD) and docking simulation on rat 3D modelled structure have been completed, in its closed and open conformation state and in complex with Quercetin, 5-Hydroxyflavone and Rutin flavonoids. Our study showed that only Quercetin and 5-Hydroxyflavone were responsible for a significant down-regulation of the Kir6.1 activity, stabilising it in a closed conformation. This hypothesis was supported by in vitro experiments demonstrating that Quercetin and 5-Hydroxyflavone were capable to inhibit K_ATP currents of rat tail main artery myocytes recorded by the patch-clamp technique.

Conclusion

Combined methodological approaches, such as molecular modelling, docking and MD simulations of Kir6.1 channel, used to elucidate flavonoids intrinsic mechanism of action, are introduced, revealing a new potential druggable protein site.

Discovery of novel antimicrobial peptides: A transcriptomic study of the sea anemone Cnidopus japonicus

As essential conservative component of the innate immune systems of living organisms, antimicrobial peptides (AMPs) could complement pharmaceuticals that increasingly fail to combat various pathogens exhibiting increased resistance to microbial antibiotics. Among the properties of AMPs that suggest their potential as therapeutic agents, diverse peptides in the venoms of various predators demonstrate antimicrobial activity and kill a wide range of microorganisms. To identify potent AMPs, the study reported here involved a transcriptomic profiling of the tentacle secretion of the sea anemone Cnidopus japonicus. An in silico search algorithm designed to discover toxin-like proteins containing AMPs was developed based on the evaluation of the properties and structural peculiarities of amino acid sequences. The algorithm revealed new proteins of the anemone containing antimicrobial candidate sequences, and 10 AMPs verified using high-throughput proteomics were synthesized. The antimicrobial activity of the candidate molecules was experimentally estimated against Gram-positive and -negative bacteria. Ultimately, three peptides exhibited antimicrobial activity against bacterial strains, which suggests that the method can be applied to reveal new AMPs in the venoms of other predators as well.

Structural basis of TRPV5 channel inhibition by econazole revealed by cryo-EM

The transient receptor potential vanilloid 5 (TRPV5) channel is a member of the transient receptor potential (TRP) channel family, which is highly selective for Ca2+, that is present primarily at the apical membrane of distal tubule epithelial cells in the kidney and plays a key role in Ca2+ reabsorption. Here we present the structure of the full-length rabbit TRPV5 channel as determined using cryo-EM in complex with its inhibitor econazole. This structure reveals that econazole resides in a hydrophobic pocket analogous to that occupied by phosphatidylinositides and vanilloids in TRPV1, thus suggesting conserved mechanisms for ligand recognition and lipid binding among TRPV channels. The econazole-bound TRPV5 structure adopts a closed conformation with a distinct lower gate that occludes Ca2+ permeation through the channel. Structural comparisons between TRPV5 and other TRPV channels, complemented with molecular dynamics (MD) simulations of the econazole-bound TRPV5 structure, allowed us to gain mechanistic insight into TRPV5 channel inhibition by small molecules.

ResQ: An Approach to Unified Estimation of B-Factor and Residue-Specific Error in Protein Structure Prediction

Computer-based structure prediction becomes a major tool to provide large-scale structure models for annotating biological function of proteins. Information of residue-level accuracy and thermal mobility (or B-factor), which is critical to decide how biologists utilize the predicted models, is however missed in most structure prediction pipelines. We developed ResQ for unified residue-level model quality and B-factor estimations by combining local structure assembly variations with sequence-based and structure-based profiling. ResQ was tested on 635 non-redundant proteins with structure models generated by I-TASSER, where the average difference between estimated and observed distance errors is 1.4Å for the confidently modeled proteins. ResQ was further tested on structure decoys from CASP9-11 experiments, where the error of local structure quality prediction is consistently lower than or comparable to other state-of-the-art predictors. Finally, ResQ B-factor profile was used to assist molecular replacement, which resulted in successful solutions on several proteins that could not be solved from constant B-factor settings.